发表机构
Chalmers University of Technology; University of Cassino and Southern Lazio; Consorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT)（查尔姆斯理工大学; 卡西诺及南拉齐奥大学; 意大利国立电信联合财团）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究针对存在时钟异步的多面板大规模MIMO场景，提出统一定位框架UNILocMP，结合几何与信道制图技术，在定位精度和鲁棒性上优于基线方法，多面板架构性能优于单面板基站部署。
AI 中文摘要
本研究提出一种名为UNILocMP的统一定位框架，该框架结合基于模型的几何方法与信道制图（CC），用于处理存在时钟异步的多面板大规模多输入多输出（MIMO）场景。得益于多面板架构，用户被分为多视距（LoS）用户（与至少两个面板保持LoS链路）和单/非视距用户（仅与一个面板或不与任何面板保持LoS链路）。针对多LoS用户，提出联合位置与时钟偏差估计方法；针对单/非LoS用户，采用两阶段数据增强策略训练无监督CC模型，其中引入了感知时钟偏差的相异性度量。数值验证表明，所提UNILocMP的性能优于基于模型和基于CC的基线方法，且与全监督指纹定位相比表现可接受。此外，在天线总数固定的情况下，与单面板基站（BS）部署相比，多面板架构显著提升了定位精度与鲁棒性，尤其在存在时钟异步的场景下优势明显。
英文摘要
In this work, we propose a unified localization framework, termed UNILocMP, that combines model-based geometry and channel charting (CC) for multi-panel massive multiple-input-multiple-output (MIMO) under clock asynchronism. Owing to the multi-panel architecture, users are classified into multi-line-of-sight (LoS) users, which maintain LoS links with at least two panels, and single/non-LoS users, which maintain a LoS link with only one panel or with none of the panels. For multi-LoS users, a joint position and clock bias estimation is developed; while for single/non-LoS users, an unsupervised CC model is trained with a two-stage data augmentation strategy, where a clock-bias aware dissimilarity metric is introduced. It is numerically validated that the proposed UNILocMP outperforms model-based and CC-based baselines and achieves acceptable performance compared with fully-supervised fingerprinting. Moreover, for a fixed total number of antennas, the multi-panel architecture significantly improves localization accuracy and robustness compared with a single-panel base station (BS) deployment, particularly in the presence of clock asynchronism.
CommentsAccepted to IEEE Globecom Workshops (GC Wkshps) 2026
